Online analytical processing (OLAP) is an integral part of most data warehouse and business analysis systems. OLAP services provide for fast analysis of multidimensional information. For this purpose, OLAP services provide for multidimensional access and navigation of the data in an intuitive and natural way, providing a global view of data that can be “drilled down” into particular data of interest. Speed and response time are important attributes of OLAP services that allow users to browse and analyze data online in an efficient manner. Further, OLAP services typically provide analytical tools to rank, aggregate, and calculate lead and lag indicators for the data under analysis.
In OLAP, information is viewed conceptually as cubes, consisting of dimensions, levels, and measures. In this context, a dimension is a structural attribute of a cube that is a list of members of a similar type in the user's perception of the data. Typically, hierarchy levels are associated with each dimension. For example, a time dimension may have hierarchical levels consisting of days, weeks, months, and years, while a geography dimension may have levels of cities, states/provinces, and countries. Dimension members act as indices for identifying a particular cell or range of cells within a multidimensional array. Each cell contains a value, also referred to as a measure, or measurement.
The fact that OLAP refers to “online” as a portion of its definition means that OLAP reporting is typically done at the server level. Data for populating the OLAP cube is pulled from a SQL database and put into cubes via a server that manages multidimensional cubes of data for analysis. While, data in the SQL database is populated as it comes in, usually the cube creation is done as a batch job, either overnight or during another low processing period. Accordingly, the data generation and cube generation processes are unconnected processes that occur separately. One example of such a server is MICROSOFT SQL SERVER Analysis Services, which is a middle-tier server for OLAP cube processing and data mining. The functionality included in these types of servers organizes data from a data warehouse into cubes with pre-calculated aggregation data. Functionality is also provided to generate data mining models from both multidimensional and relational data sources. The server is able to be accessed by reports, such as a PIVOTTABLE report included in the MICROSOFT EXCEL spreadsheet software. These structured reports retrieve data from the server and present it to the user.